Alternatives and similar repositories for GA_for_Feature_Selection

Users that are interested in GA_for_Feature_Selection are comparing it to the libraries listed below

• rogeroyer / feature_selection_GAAlgorithm
  基于遗传算法的特征选择
  ☆127Updated 5 years ago
• Albertsr / Class-Imbalance
  Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.
  ☆107Updated 4 years ago
• weepon / feature_selection
  常用的特征选择方法
  ☆68Updated 3 years ago
• ShaoQiBNU / stacking
  集成学习Stacking方法详解
  ☆75Updated 5 years ago
• felix-last / kmeans_smote
  Oversampling for imbalanced learning based on k-means and SMOTE
  ☆127Updated 4 years ago
• syxiaa / RSMOTE
  Oversampling method based on relative density
  ☆13Updated 4 years ago
• Alxe1 / FeatureSelectionsAndExtractions
  feature selections and extractions
  ☆88Updated last year
• xuman-Amy / preprocessing
  数据预处理之缺失值处理，特征选择
  ☆21Updated 6 years ago
• bvshyam / ctgan_tabular_data
  Creating tabular GAN on credit card dataset
  ☆20Updated 5 years ago
• CLaraRR / autoencoder_practice
  AutoEncoder implements by keras. Including AE, DAE, DAE_CNN, VAE, VAE_CNN, CVAE, Sparse AE, Stacked DAE.
  ☆41Updated 5 years ago
• aBadCat / machineLearning
  Learning and Recording
  ☆34Updated 5 years ago
• qiuhaining / sklearn-SVM
  支持向量机(SVM)——分类预测，包括多分类问题，核函数调参，不平衡数据问题，特征降维，网格搜索，管道机制，学习曲线，混淆矩阵，AUC曲线等
  ☆52Updated 7 years ago
• shiluqiang / WLSSVM_python
  Weighted LSSVM for regression
  ☆38Updated 6 years ago
• helenzhao093 / MLMethods
  Implementations of various feature selection methods
  ☆24Updated 4 years ago
• iamyuanchung / csdnn
  Theano implementation of Cost-Sensitive Deep Neural Networks
  ☆26Updated 7 years ago
• LitoNeo / pytorch-AutoEncoders
  Autoencoders in PyTorch
  ☆101Updated 5 years ago
• LiangjunFeng / Broad-Learning-System
  BLS Code
  ☆123Updated 6 years ago
• zhulei227 / ML_imblearn
  类别不平衡学习，包括采样、代价敏感学习、决策输出补偿以及集成学习等内容
  ☆36Updated 4 years ago
• zhaoxingfeng / RandomForest
  随机森林，Random Forest（RF）
  ☆406Updated 5 years ago
• OlaWod / feature-selection_GA-SA
  Use Genetic Algorithm and Simulate Anneal for feature selection. 用遗传算法/模拟退火算法进行特征选择.
  ☆30Updated 5 years ago
• luanshiyinyang / DataMiningProject
  包含一些比较常见的数据挖掘竞赛或者项目的源码
  ☆129Updated 6 years ago
• BackyardofAbela / EnsembleLearning
  包括决策树和随机森林进行离职人员预测，Xgboost和lightGBM的应用
  ☆289Updated 5 years ago
• lyx199504 / param-opt
  本项目开发了一个机器学习和深度学习的训练工具。该训练工具基于sklearn和pytorch，不仅支持常规训练、交叉验证训练，还支持贝叶斯搜索参数，并可随时自动保存训练模型和日志。
  ☆12Updated last year
• Albertsr / Anomaly-Detection
  UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.
  ☆298Updated 4 years ago
• ideasplus / imbalance-learning
  There are some reproduced algorithms for learning from imbalanced data, including over-sampling,under-sampling and boosting
  ☆12Updated last year
• realWang-Wei / BroadLearningSystem
  here is the introduce of bls
  ☆69Updated 4 years ago
• ahcantao / PSOFeatureSelection
  A Particle Swarm Optimization (PSO) for Feature Selection. Using PySwarm.
  ☆53Updated 7 years ago
• JinJunRen / GB-SMOTE
  This method is a new oversampling algorithm and can circumvent the deficiency of WK-SMOTE (and SMOTE as well as its variants) caused by r…
  ☆16Updated 2 years ago
• ZhiningLiu1998 / self-paced-ensemble
  [ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架
  ☆259Updated last year
• LiangjunFeng / Tri-training
  The python implementation of tri-triaing
  ☆50Updated 6 years ago